Unraveling the multi-targeted curative potential of bioactive molecules against cervical cancer through integrated omics and systems pharmacology approach

Molecular level understanding on the role of viral infections causing cervical cancer is highly essential for therapeutic development. In these instances, systems pharmacology along with multi omics approach helps in unraveling the multi-targeted mechanisms of novel biologically active compounds to combat cervical cancer. The immuno-transcriptomic dataset of healthy and infected cervical cancer patients was retrieved from the array express. Further, the phytocompounds from medicinal plants were collected from the literature. Network Analyst 3.0 has been used to identify the immune genes around 384 which are differentially expressed and responsible for cervical cancer. Among the 87 compounds reported in plants for treating cervical cancer, only 79 compounds were targeting the identified immune genes of cervical cancer. The significant genes responsible for the domination in cervical cancer are identified in this study. The virogenomic signatures observed from cervical cancer caused by E7 oncoproteins serve as the potential therapeutic targets whereas, the identified compounds can act as anti-HPV drug deliveries. In future, the exploratory rationale of the acquired results will be useful in optimizing small molecules which can be a viable drug candidate.

www.nature.com/scientificreports/ Mining of immune responsive genes of human transcriptome related to cervical cancer. The human transcriptomic datasets of cervical cancer cases were collected from the Array express database (https:// www. ebi. ac. uk/ array expre ss/) with the ID: E-GEOD-39001 and E-GEOD-46842 31 which encodes the affymetrix data. This data has been manually curated using excel Microsoft. Upon completion of the curation, the transcriptomic datasets was then imported into the Network Analyst 3.0. database (https:// www. netwo rkana lyst. ca/) especially to the Gene expression table to check the total number of genes 32 . The dataset is generally saved in the .txt file format which is plotted in the excel file with the microarray data intensities corresponding to the immune responsive genes of healthy controls and cancer patients. These data are depicted in the time series of columns and rows in the excel data format as sample and class. Followed by the incorporation of the dataset, normalization and filtering is carried out for making certain that the distribution of expression is comparable across the inclusive experiments and to remove the inconsistent data, respectively. Further, the differential gene expression analysis is carried out to witness the significant immune genes which are responsive through the Limma statistical model with the adjusted P-value less than 0.05 along with the representation of 1.0 as Log2 fold change value. The identified genes were further studied for the over representation analysis (ORA) functional enrichment along with the tissue-specific interactions through the inbuilt databases in Network Analyst 3.0. In order to make the results more clear, the probe set ID has been referred through the BioGPS database (http:// biogps. org/ datas et/) and the gene name was confirmed 32 and provided in Supplementary Table S1.
Pharmacologically active phytocompounds. Exhaustive information on the pharmacologically active molecules from the plants M. indica, N. sativa, Z. officinale, C. grandis, Z. jujube, Z. mauritiana and C. cassia were retrieved from the web sources and literature [22][23][24][25][26][27][28][29][30]33 . List of the active compounds from the natural medicinal plants with their abbreviations were given in Table 1. The information like the canonical SMILES of the compounds was retrieved from the PubChem database (https:// pubch em. ncbi. nlm. nih. gov/) 34 are also provided in Table 1. The identified compounds from the medicinal plants were searched against the Homo sapiens in SwissTargetPrediction tool (http:// swiss targe tpred iction. ch/ index. php) in order to retrieve the human targets especially the immune responsive genes 35 .

Compound target network (CTN) construction and features of human targets. The construc-
tion of the CTN illuminates the multi-target therapeutic features of the pharmacologically active plant compounds. In this construction, we observed, the interaction between the human immune-responsive genes and the phytocompounds representing the interconnection which is visualized through the Cytoscape v3. 8.0. In the obtained interactome, the node depicts the compounds and targets whereas the edge denotes the molecular interaction between the compounds and targets 36 . The significant 35 immune responsive genes/targets obtained from the literature and CTN analysis were used for the retrieval of molecular features like official Gene Symbol with the name, position of the target, chromosome numbers and orthologs of the differentially expressed immune responsive genes from the NCBI-gene database (https:// www. ncbi. nlm. nih. gov/ gene) and The Human Protein Atlas (https:// www. prote inatl as. org/) 19,37 .
Pharmacological features of the compounds. The compounds with the respective canonical SMILES were subjected to the Molinspiration online tool (https:// molin spira tion. com/) in order to obtain significant molecular features of the phytocompounds. Along with this the bioactive score for the vital targets such as the GPCR ligand activity, protease inhibitor activity (Pi), Kinase Inhibitor activity (Ki) and number of violations (nVio) were predicted 38-40 . Gene ontology enrichment analysis. The genes which are differentially expressed with the encoding gene symbols were uploaded to the GOnet (https:// tools. dice-datab ase. org/ GOnet/) and Metascape (https:// metas cape. org/ gp/ index. html#/ main/ step1) databases in order to attain the ontology against the humans with the significant threshold of q-value which is greater than 0.05. The immune-responsive genes were pigeonholed with the molecular function and biological process based on the functional enrichment classification of the database 35 .
Construction of protein-protein interaction (PPI) Network associated with HPV 16 E7 and other cancer associated proteins. The cellular machinery of the proteins is formed based on the interactions made by the proteins. Recognition of the PPI perseveres to be one of the foremost determinations in modern biology as well as the improvement of protein therapeutics 41 . In our study, we attempted to identify the interactions between the oncoprotein of E7 and the dominated therapeutic proteins of human. The STRING database (https:// string-db. org/) is used for the identification of the human proteins interacting with the obtained immune-responsive genes by providing the input manually obtained from the CTN 42 . The STRING database depicts the interactions between proteins which compasses direct interaction physically and the indirect correlation representing the functional aspects of the protein 43 . The information obtained from the database regarding the PPI is curated from the experimental data, prediction from the genomic features, text mining from the scientific articles and from various database 44 . This database provides the score based on the weight and impact of the interactions 45   www.nature.com/scientificreports/

Results
Immune responsive genes from Meta-analysis of human immunotranscritpome. The transcriptomics dataset contains 8353 immune responsive genes which are diversified into 59 samples out of which 3680 genes were commonly found in the meta differential expression depicted in Fig. 1. Figure 1 states that, immune responsive genes that are up, down and non-significantly expressed. Followed by the interactive volcano plot, heat map profiling revealed that 384 immune responsive genes were expressed differentially in cervical cancer cases during various time periods when compared with the healthy controls which are clearly evident in Supplementary Fig. 1. The genes that are up and down regulated among the 384 genes were listed in Supplementary  Table S2. The differentially expressed genes are visualized through the tissue specific PPI in the tissue type whole blood represented in Fig. 2. This network encompasses 4184 nodes and 8064 edges. Further, the pathway-based ORA enrichment network showed involvement in various biological pathways which is represented in Fig. 3.

Retrieval of information regarding phytocompounds.
A total of 87 molecules were retrieved through the literature and employed as a query in the PubChem database to fetch the canonical SMILES which are represented in Table 1 along with the abbreviations. The abbreviations mentioned were further used during the CTN construction. The obtained information about the compound was used further for the biomolecular analyses.  www.nature.com/scientificreports/   www.nature.com/scientificreports/ Pharmacologically active compounds and its interaction with human targets. The active phytocompounds that direct towards the human immune receptors were computed through the SwissTargetPrediction tool. Among the 87 compounds, 79 compounds were appreciably targeting 35 out of the 384 human immune-responsive and literature-retrieved receptors/genes that are differentially expressed between healthy and cancer cases. The comprehensive list of the phytocompounds and the equivalent interaction with the human immune responsive genes are provided in Table 2. Properties of the human immune responsive genes. A total of 35 immune responsive genes have been targeted by 79 phytocompounds. The corresponding information on the immune receptors namely chromosome number, the full name of the genes, physical position and the orthologs details were obtained and provided in Table 3. This information paves way for the delineation of the detailed molecular function. Further, the pictorial representation of the significant gene and its involvement in various biological pathways were presented in Supplementary Fig. S2.  www.nature.com/scientificreports/ Gene ontology enrichment analysis. The molecular features of the considerable HPV infected cervical cancer immune responsive genes interacting with compounds were further analyzed with the Metascape which revealed the involvement of these immune genes in different molecular functions and biological processes. The targeted immune-responsive genes and the corresponding proteins were attributed to be involved in the crucial biological regulation of signal transduction, cell population proliferation, cellular metabolic processes, proteolysis, cell communication, apoptosis, response to stress, catabolic process and oxidative process. These processes of biological regulation with the 35 immune genes were strongly evident in Fig. 5. The Molecular functions of the selected 35 immune genes targeted by compounds were represented in Supplementary Fig. S3 stating that the immune targets are responsible for catalytic activity and the histone deacetylases binding. Followed by the molecular function, the enrichment network analysis carried out with the Metascape database is represented in Supplementary Fig. S4 stating the involvement in various biological pathways. The histogram corresponding to the enriched pathways in relation to the identified 35 genes was represented in Fig. 6 and differentiated based on the cluster ID with saturated colors. Further, the 35 genes were analyzed for the tissue-specific PPI observed for the whole blood tissue type. These interactions are depicted in Fig. 7.

Molecular interactome analysis.
A total of 35 genes including the cervical cancer immune genes retrieved from the compound network analysis and the literature reported which is differentially expressed www.nature.com/scientificreports/ between the healthy and the affected cases demonstrated the molecular cross-talks. The interactome possessess 75 nodes and 1101 edges represented in the Fig. 8. The average nodal degree of the immune responsive genes analyzed for the interactome is 29.4 in the closely connected immune proteins/genes. The enrichment score of the PPI for the immune responsive genes possesses p-value score of < 1.0e. 16. These interactions also showed the complexity and functionalities of the cervical cancer responsive immune genes provided the potential targets for therapy against cancer. Additionally, the immune-responsive genes that interact with the HPV E7 obtained from the transcriptomic data were also identified for the molecular interaction between various human proteins which is represented in Fig. 9. This study clearly indicates that HPV E7 interacts with various cancer target proteins and represents those human proteins to be a potential target for drug discovery.
Pharmacological features of the phytocompounds. The phytocompounds obtained from the literature reported for various biologically active plants have been calculated for their pharmacological properties such as the GPCR, Pi, Ki, Ncr, Ei, nVio which are represented in Table 4. The nVio and Ei has been considered to be significant with a threshold of above 0.5 feature score. Around 30 compounds are considered to be more efficacious that can be used further for the treatment of cervical cancer. The pharmacological features such as GPCR, Pi, Ki, Ncr, Ei, nVio influences the oral bioavailability, solubility and permeability of drug. These features were predicted through the experimentally validated computational approaches in accordance with the Rule of 5 (Ro5) drug discovery.

Discussion
Cancer has been represented to be the most widespread cause of mortality worldwide which leads to millions of deaths every year. This has been caused by various infections by different microorganisms among which viral infections catch hold of 20 percent importance and represent a significant function in the development Numerous drugs and vaccines are reported for the treatment of cervical cancer but the ineffectiveness of the anti-HPV drugs to medicate the harmful infection provoked us to identify the novel compounds that are effective in the control and treatment of the cancerous growth in humans. Alongside, the use of traditional medicines is known for decades in the treatment of various diseases in this world through the ancient medical practices 49 . Even though, the chemical composition of the medicinal plants has been obtained for the flawless drug development, this aspect is not confident enough due to the higher insolence of chemical entities and the functional aspects of the drug statute 33,50 . Researchers have reported that traditional medicines were proven to be effective to treat the infections and diseases caused by viruses like HIV, measles, hepatitis, coxsackievirus and HPV 50 . These observations on the viral oncoproteins and the role of plant compounds provided more insights into the understanding of the interaction with the human physiological system through the control of molecular cross-talks between the key elements in the immunological aspects. Further, the exact mechanism of the immune responsive targets and the impression of herbal medicines to treat viral infections is inadequate still 35 . With this as pilot information, we presented the immuno-transcriptomics and systems pharmacology strategies to unravel the immune targets of HPV and the associated signaling pathways along with the pharmacological roles of M. indica, N. sativa, Z officinale, C. grandis, Z. jujube, Z. mauritiana and C. cassia derived bioactive compounds for the treatment of www.nature.com/scientificreports/ HPV related cancerous growth at molecular level. Additionally, the information on the bioactive molecules derived from the natural plants for the treatment of viral disease provides vital information on therapeutics.
Our study is mainly focused on the identification and understanding of the pattern related to the gene expression of the host which is responsible for cervical cancer. Our investigation lies with the performance of the immuno-transcriptomics profiling between the infected and healthy controls with the transcriptomics dataset available in the public databases. These datasets were further processed with the Network Analyst 3.0 which helps in the retrieval of heatmap representing the intensities of microarray in cervical cancer immune genes. Based on this analysis, a total of 384 immune responsive genes between the healthy and infected patients were obtained with the intensity values. Further, these genes were selected for the successive analysis of the PPI. On the other hand, PubChem and other omics databases help in identifying 87 phytocompounds that are responsible for treating cervical cancer. Among the 87 phytocompounds, 79 compounds interacted with the 35 differentially expressed cervical cancer associated immune genes through drug targeting. The compounds that interact with the immune responsive genes were represented in Table 2 which shows that only 35 immune genes are involved in the process of drug targeting among the 87 phytocompounds. Remarkably, the predicted immune genes which are involved in the different biological activities against cervical cancer has been identified and some of the genes obtained from network analyst are not reported till date which exhibits the capability of SwissTargetPrediction and the gene ontology enrichment evaluation methods. Further, the ORA functional enrichment of the identified genes was demarcated with the help of Metascape. The analysis of the compounds that target the human genes which are expressed differentially highlights the role of 35 genes among the identified 384 genes and the literature    www.nature.com/scientificreports/ reported receptors. The immune-responsive genes PTPN14, CDK2, HDAC9, MMP2, AURKA, PARP1 and GRIA depicts their role in most of the diseases targeting humans among the highlighted 35 components. The genes CDK2, HDAC9 and PTPN14 interact commonly with the phytocompounds that target the immune responsive and also with the HPV E7 oncoprotein which is strongly evident in Fig. 9. For instance, PTPN14 (Protein Tyrosine Phosphatase Non-Receptor Type 14) is the potential tumor suppressor which owns its involvement in the linkage to the control of Hippo and the Wnt/beta-catenin signaling pathways. Herein, we understood that the cross-talk between HPV E7 and PTPN14 might be the important reason for immune-pathological expression of cervical cancer 51 . The genes which have been commonly targeted by various phytocompounds are significantly playing a noteworthy role in different viral infections and are also responsible for other cancers/diseases. The correlation between the host immune response to catalytic activity and the histone deacetylases binding is identified through the classification of molecular functions. The obtained results revealed that, the immune response between infections and cervical cancer is highly significant at the biological level. As per our earlier discussion, the role of PTPN14, CDK2 and HDAC9 in tumor suppression and the interaction with HPV E7 oncoprotein is observed stating that these targets can be potential druggable targets for cervical cancer. Additionally, functional enrichment and the gene ontology revealed its strong relation to apoptosis and other pathways in cancer. The molecular interactome analysis between the viral oncoprotein and the components of human immune response demonstrates the critical capability of viral replication to dodge the immunological responses. The compound target network analysis revealed that the retrieved 79 among 87 compounds strongly bind with the identified 35 compounds representing its ability to inhibit the progression of any diseases. Further, the cytoscape analysis revealed the interaction between the phytocompounds and the human immune genes which is the essential identification of this study. This study unveils the diversified mechanism of the compounds and the plausible mode of action towards assorted targets involved in cancer. These inferences help us to put forth the curative effects and promote the use of traditional medicines that leads to make novel avenues in the field of drug discovery and development. Further, it impacts the people's lives by providing the drugs at low cost. www.nature.com/scientificreports/

Conclusion
The results from our study reveals that the Indian traditional phytocompounds including a variety of medicinal values exhibits the expanded immunological stimulants to treat cervical cancer caused by the infection of HPV E7. The research on the traditional Indian medical plants notably on M. indica, N. sativa, Z. officinale, C. grandis, Z.jujube, Z. mauritiana and C. cassia is not explored completely. Radically, our result on the phytocompounds with the pharmacological properties represents the interaction with the human immune responsive genes along with their role in various biological processes and function. These studies overlay the groundwork for the aperture of advanced biological research on different types of cancer with the combination of traditional medicines. This study identified the several crucial aspects of the host immune response towards the infection of HPV E7 oncoprotein. The identified immune responsive genes and the corresponding signaling pathways help in unraveling the pathogenesis of cervical cancer. Also, these analyses help in the characterization of the immunopathology of the HPV E7 infection. Our study is mainly focused on the conjecturing the use of phytocompounds in combination with other components may provide synergistic effects which may lead to further development of new anti-HPV or anti-cancer drugs. Additionally, the molecular interactome analysis reveals that thirty-eight immune responsive genes can be considered the effective druggable targets for the treatment of various cancer and other diseases. On the whole, this comprehensive study behaves as the stage to improve the understanding of the immunological behavior of the HPV E7 oncoprotein which also provides the widespread knowledge in executing the intrusion approach.  www.nature.com/scientificreports/

Data availability
The datasets generated and/or analyzed during the current study are not publicly available since the continuation of the work has not been published but are available from the corresponding author on reasonable request.